Evolutionary Multi-Objective Optimization for Web Service Location Allocation Problem

With the ever increasing number of functionally similar web services being available on the Internet, the market competition is becoming intense. Web service providers (WSPs) realize that good Quality of Service (QoS) is a key of business success and low network latency is a critical measurement of good QoS. Because network latency is related to location, a straightforward way to reduce network latency is to allocate services to proper locations. However, Web Service Location Allocation Problem (WSLAP) is a challenging task since there are multiple objectives potentially conflicting with each other and the solution search space has a combinatorial nature. In this paper, we consider minimizing the network latency and total cost simultaneously and model the WSLAP as a multi-objective optimization problem. We develop a new PSO-based algorithm to provide a set of trade-off solutions. The results show that the new algorithm can provide a more diverse range of solutions than the compared three well known multi-objective optimization algorithms. Moreover, the new algorithm performs better especially on large problems.

Automated summary

As the number of functionally similar web services on the Internet continues to increase, market competition has become intense. Web service providers recognize that good Quality of Service (QoS) is crucial for business success, with low network latency being a key indicator of good QoS. This paper addresses the challenges of the Web Service Location Allocation Problem (WSLAP) by developing a new PSO-based algorithm that can provide a wider range of solutions compared to existing multi-objective optimization algorithms, particularly performing better on larger scale problems.